This disclosure relates to a system for monitoring a person suffering from a chronic medical condition in order to predict and assess physiological changes which could affect the care of that subject. Examples of such chronic diseases include (but are not limited to) heart failure, chronic obstructive pulmonary disease (COPD), asthma, and diabetes.
To provide a context for the limitations of conventional approaches, it is instructive to briefly review current approaches to chronic disease monitoring for three major diseases: heart failure, COPD and asthma.
Heart failure (HF) is a relatively common and severe clinical condition, characterized by the inability of the heart to keep up with the oxygen demands of the body. Management of heart failure is a significant challenge to modern healthcare systems due to its high prevalence and severity. It is estimated that heart failure accounts for approximately 2-3% of the entire healthcare budget of developed nations, and is the number one cause of hospitalization of the over-65 s in the USA.
Heart failure is a chronic condition, which is progressive in nature. Physicians typically class the severity of the disease according to a New York Heart Association (NYHA) subjective grading system from 1 to 4, where 4 is the most severe case. Heart failure can also be further broken into classes such as systolic and diastolic heart failure. The progression of heart failure is often characterized as relatively stable over long periods of time (albeit with reduced cardiovascular function) punctuated by episodes of an acute nature. In this acute phases, the patient experiences worsening of symptoms such as dyspnea (difficulty breathing), gallop rhythms, increased jugular venous pressure, and orthopnea. This is typically accompanied by overt congestion (which is the build up of fluid in the pulmonary cavity). This excess fluid often leads to measurable weight gain of several kilograms. In many cases, however, by the time overt congestion has occurred, there are limited options for the doctor to help restabilize the patients, and in many cases the patient requires hospitalization.
There already exist some approaches to the detection of clinical deterioration, but with limitations. For example, a range of chronic disease management programs have been developed to improve the healthcare response to HF, with an emphasis on both increased patient care and reduced cost. Critical components of successful programs include a) patient education, b) telemonitoring of physiological measurements and symptoms, c) sophisticated decision support systems to use the reported symptoms and measurements to predict clinically significant events, and d) a focus on individualized care and communication (e.g., “teaching in the moment” in response to events affecting a patient's health).
However, accurate diagnosis of clinical deterioration in heart failure can be quite difficult. In particular, prevention of overt congestion which often requires hospitalization, is of particular importance. Weight measurement has been shown to be a reasonably reliable physiological guide to heart failure deterioration. This can lead to reduced mortality, when combined with other accepted strategies for heart failure management. Moreover, weight management has the additional psychological benefit of involving the patient directly in their own care, as well as being simple and low-cost.
However, despite the widespread use of recommendations on weight gain as a marker of deterioration (e.g., a patient is told that a gain of 2 kg over a 2 to 3 day period should generate a call to their clinic), there is relatively little published data on the sensitivity and specificity of ambulatory monitoring of weight gain in a clinical setting. Groups who have investigated the sensitivity of weight gain in distinguishing clinically stable (CS) Class IV patients from those with clinical deterioration (CD), have found that the performance is quite limited. These researchers found quite modest predictive values for weight gain in isolation. For example, the clinical guideline of 2 kg weight gain over 48-72 h has a specificity of 97% but a sensitivity of only 9%. Reducing the threshold to 2% of body weight, improves the sensitivity to 17% (with specificity only dropping marginally). In general they conclude that weight gain in isolation has relatively poor sensitivity in detecting clinical deterioration (though its specificity is good).
Thus, what is needed is a system and method to overcome the current limitation on the sensitivity of weight gain to predict clinical deterioration.
Measurement of B natriuretic peptides (BNP) has also been suggested as a viable tool for assessment of heart failure status; this could be implemented at a primary care or outpatient clinic setting using point-of-care devices, though at present it can not be clinically deployed on a daily monitoring basis. In a report on BNP monitoring, researchers reported a sensitivity of 92% on a population of 305 subjects, but with a specificity of only 38%. While this is a promising approach, there are significant practical issues around providing point-of-care assays for BNP in community care due to cost, training and patient convenience. Accordingly, there remains a need for development of improved low-cost convenient diagnostic markers of clinical deterioration of heart failure which can be deployed in the patient's day-to-day environment.
Thus, what is needed is a system and method to improve the specificity of detecting clinical deterioration as compared to approaches such as BNP monitoring, and for such systems to be convenient for patient use in their home environment.
Some potential markers of clinical deterioration in heart failure are changes in nocturnal heart rate, changes in sleeping posture, and changes in respiration. In particular, heart failure is highly correlated with sleep disordered breathing (SDB), though the causality mechanisms are not well understood. For example, in a recent study in Germany, 71% of heart failure patients have an Apnea-Hypopnea index greater than 10 per hour (with 43% having obstructive sleep apnea and 28% having primarily Cheyne-Stokes respiration (periodic breathing). Other researchers reported a prevalence of 68% in their HF population in a New Zealand study. Significant sleep disordered breathing has been reported to correlate with poor outcomes in heart failure; however, no study has yet been able to track changes in respiratory patterns over time to see how it varies with clinical stability. For example, in the Home or Hospital in Heart Failure (HHH) European-wide study, overnight respiratory recording (using respiratory inductance plethysmography) was carried out for a single night at baseline in 443 clinically stable HF patients. Apnea Hypopnea Index and Duration of Periodic Breathing were shown to be independent predictors of cardiac death and hospitalization for clinical deterioration. However no practical system for assessing these respiratory parameters on a nightly basis was available for these researchers.
Measurement of nocturnal heart rate and heart rate variability can also aid in the detection of clinical deterioration in heart failure.
A second chronic medical condition for which the current system can be used is Chronic Obstructive Pulmonary Disease (COPD). COPD is a disease of the lungs in which the airways are narrowed, which leads to a restricted flow of air to the lungs. COPD is currently the fourth leading cause of death in the USA, and its estimated cost to the healthcare system is $42.6 billion in 2007. It is associated with dyspnea (shortness of breath) and elevated breathing rates (tachypnea). As for heart failure, there can be acute exacerbations of COPD, often due to bacterial or viral infections. However, definitions of what exactly constitutes an exacerbation, and means to accurately predict it are a subject of active research in the medical community. For example, tracking of C-reactive protein or measurements of inspiratory capacity have been proposed as means to predict exacerbations. Changes in peak expiratory flow have been considered for prediction of clinical deterioration, but are considered insufficiently sensitive.
Thus what is needed is a reliable method for accurately recognizing exacerbations in COPD patients. Further, what is needed is a system and method for recognizing clinical deterioration in COPD patients through tracking of respiratory patterns.
Respiratory rate is a key indicator of the severity of COPD. For example, normal healthy adults may have respiratory rates which are about 14-16 breaths/minute while asleep; the resting respiratory rate of a person with severe COPD (but not in acute respiratory failure) may be in the range 20-25 breaths/minute, while in an acute respiratory failure, this rate may increase to more than 30 breaths/minute. Accordingly a system for simple monitoring of respiratory rate has utility in assessing the status of subjects with COPD. However, current systems for monitoring respiratory rate are typically based on measurement of airflow using nasal cannulae or respiratory effort belts and are not used for continuous monitoring of respiratory patterns in the person's own environment due to comfort and convenience issues. Thus what is needed is a system for tracking exacerbations in COPD patients which does not require the subject to wear an oro-nasal cannula or chest belt.
An additional chronic medical condition is asthma. This is a common chronic condition in which the airways occasionally constrict, become inflamed, and are lined with excessive amounts of mucus, often in response to one or more triggers, such as smoke, perfume, and other allergens. Viral illnesses are also a possible trigger, particularly in children. The narrowing of the airway causes symptoms such as wheezing, shortness of breath, chest tightness, and coughing. The airway constriction responds to bronchodilators. Between episodes, most patients feel well but can have mild symptoms and they may remain short of breath after exercise for longer periods of time than an unaffected individual. The symptoms of asthma, which can range from mild to life threatening, can usually be controlled with a combination of drugs and environmental changes. The estimated prevalence of asthma in the US adult population is 10%, so it represents a significant public health issue. As for HF and COPD, the disease is marked by sudden exacerbations.
A key marker of asthma is peak expiratory flow (PEF)—this can be obtained from the patient by asking them to blow into a spirometer. However spirometry only gives point measurements of function, and also requires the active involvement of the subject, and so is not suited for young children. Researchers have previously noted a link between PEF and respiratory rate. Accordingly what is needed is a system and method for monitoring respiratory rate in subjects with asthma.
Furthermore other disease conditions such as cystic fibrosis, pneumonia, corpulmonale and infection caused by the respiratory syncytial virus (RSV) may all be better monitored by a system capable of monitoring respiratory rate and/or nocturnal heart rate.